Hyperanalytic denoising

A new threshold rule for the estimation of a deterministic image immersed in noise is proposed. The full estimation procedure is based on a separable wavelet decomposition of the observed image, and the estimation is improved by introducing the new threshold to estimate the decomposition coefficients. The observed wavelet coefficients are thresholded, using the magnitudes of wavelet transforms of a small number of "replicates" of the image. The "replicates" are calculated by extending the image into a vector-valued hyperanalytic signal. More than one hyperanalytic signal may be chosen, and either the hypercomplex or Riesz transforms are used, to calculate this object. The deterministic and stochastic properties of the observed wavelet coefficients of the hyperanalytic signal, at a fixed scale and position index, are determined. A "universal" threshold is calculated for the proposed procedure. An expression for the risk of an individual coefficient is derived. The risk is calculated explicitly when the "universal" threshold is used and is shown to be less than the risk of "universal" hard thresholding, under certain conditions. The proposed method is implemented and the derived theoretical risk reductions substantiated

Archaeological evaluation : Skelhorne Street, Liverpool

Salford Archaeology was commissioned by Nexus-Heritage to undertake an archaeological evaluation on a car park at Skelhorne Street and Bolton Street, Liverpool (centred on NGR 335075 390430) as part of a redevelopment scheme. This report consists of the results from the three evaluation trenches excavated during the course of this work. An archaeological assessment had demonstrated that the study area had the potential for the survival of remains relating to an 18th century bath house, an 18th century steam powered textile mill and a series of 18th and 19th houses depicted on mapping of 1803 and 1848. The trenches within the current study area revealed that bedrock was very close to the surface at the southern end of the site. Trench 2 uncovered the edge of a mid 19th century brick built house that had been constructed over a former rock cut well that is likely to have originally served the 18th century bath house. Both trenches 1 and 3 uncovered remains of a 20th century bus station in the form of a ring beam, concrete floor slab, column bases and a tiled floor. Trench 1, in the northern half of the site showed that the area had used compacted rubble from the demolition of the bus station to level the site prior to having tarmac laid down for the car park. The demolition material contained possible ACMs and so progress in this area had to be ceased. The results obtained from the evaluation trenches have indicated that the ground level, originally a hill sloping downwards from southeast to northwest, had bee significantly reduced in the southeast of the site, cutting into the bedrock by over 3m. The ground reduction lessened downslope and the northwest corner of the area had been built up to create a level car park. This meant that any remains in the east, southeast and south of the site had been removed entirely. As the houses ran downslope to the northwest the chance of cellars surviving increases with the floor of a cellar exposed in trench 2. It may be that deeper cellars exist towards the northwest of the site area but the presence of possible ACMs in the overburden precludes further excavation in this area at present

Archaeological evaluation : Store Street, Ancoats, Manchester

In March 2017, Salford Archaeology was commissioned by CgMs Consulting to carry out an archaeological evaluation of land between Store Street and Millbank Street in the Ancoats area of Manchester (centred on NGR 385150 398175). The evaluation was carried out in accordance with a Written Scheme of Investigation produced by CgMs Consulting in June 2016, and was required to fulfil a condition (Condition 12) placed on planning consent for the redevelopment of the site (Planning Ref: 110276/FO/2015/C2). The archaeological interest in the site was highlighted in a desk-based assessment that was produced by WSP|Parsons Brinckerhoff in 2015. This concluded that there was potential for archaeological remains relating to the early 19 th -century Ardwick and Ancoats Dispensary and a mid-19 th -century iron foundry and copper works to survive insitu. The archaeological evaluation comprised the excavation of two 30m long trenches, which were targeted on the footprint of the former iron foundry and copper works in the central part of the site (Trench 1) and the Ardwick and Ancoats Dispensary to the north-east (Trench 2). The only archaeological features observed in the excavated trenches, however, comprised a short section of a 20 th -century wall in Trench 1, and a wood-lined circular feature with an associated brick surface in Trench 2. Both of these features were truncated and fragmentary, and were overlain by a homogenous mixed demolition rubble levelling layer, which appeared to have been deposited very recently. Based on the results obtained from the evaluation trenches, it is concluded that no further investigation is merited in advance of the construction works for the proposed development

Incremental learning with respect to new incoming input attributes

Neural networks are generally exposed to a dynamic environment where the training patterns or the input attributes (features) will likely be introduced into the current domain incrementally. This paper considers the situation where a new set of input attributes must be considered and added into the existing neural network. The conventional method is to discard the existing network and redesign one from scratch. This approach wastes the old knowledge and the previous effort. In order to reduce computational time, improve generalization accuracy, and enhance intelligence of the learned models, we present ILIA algorithms (namely ILIA1, ILIA2, ILIA3, ILIA4 and ILIA5) capable of Incremental Learning in terms of Input Attributes. Using the ILIA algorithms, when new input attributes are introduced into the original problem, the existing neural network can be retained and a new sub-network is constructed and trained incrementally. The new sub-network and the old one are merged later to form a new network for the changed problem. In addition, ILIA algorithms have the ability to decide whether the new incoming input attributes are relevant to the output and consistent with the existing input attributes or not and suggest to accept or reject them. Experimental results show that the ILIA algorithms are efficient and effective both for the classification and regression problems

Psychosocial and Biological Factors Contributing to Body Weight Gain in Schizophrenia

Overweight and obesity are frequently reported to be a significant issue in schizophrenia resulting in the inherent complications of these disorders. Body weight gain also commonly results from treatment with the most tolerable and efficacious pharmacological treatments, second-generation antipsychotics. However there are numerous other factors that contribute to increased body mass in individuals with schizophrenia prior to the initiation of treatment. With prior research indicating that individuals with schizophrenia have higher rates of overweight and obesity before treatment. Therefore this article provides a review of pertinent issues associated with body weight gain in schizophrenia in an attempt to delineate the impact of both the disease and treatment upon body weight gain. The results of the review indicate that body weight gain in schizophrenia occurs from both psychosocial and biological factors that are further compounded by antipsychotic treatment. The article concludes with recommendations for future research

Analysis and three-dimensional modeling of vanadium flow batteries

This study presents 1.) a multi-dimensional model of vanadium Redox Flow Batteries (RFB); 2.) rigorous explanation of porelevel transport resistance, dilute solution assumption, and pumping power; and 3.) analysis of time constants of heat and mass transfer and dimensionless parameter. The model, describing the dynamic system of a RFB, consists of a set of partial differential equations of mass, momentum, species, charges, and energy conservation, in conjunctionwith the electrode's electrochemical reaction kinetics. The governing equations are successfully implemented into three-dimensional numerical simulation of charging, idling, and discharging operations. The model, validated against experimental data, predicts fluid flow, concentration increase/decrease, temperature contours and local reaction rate. The prediction indicates a large variation in local reaction rate across electrodes and the time constants for reactant variation and temperature evolution, which are consistent with theoretical analysis. © 2014 The Electrochemical Society. All rights reserved

Multiple multidimensional morse wavelets

This paper defines a set of operators that localize a radial image in space and radial frequency simultaneously. The eigenfunctions of the operator are determined and a nonseparable orthogonal set of radial wavelet functions are found. The eigenfunctions are optimally concentrated over a given region of radial space and scale space, defined via a triplet of parameters. Analytic forms for the energy concentration of the functions over the region are given. The radial function localization operator can be generalised to an operator localizing any L-2(R-2) function. It is demonstrated that the latter operator, given an appropriate choice of localization region, approximately has the same radial eigenfunctions as the radial operator. Based on a given radial wavelet function a quaternionic wavelet is defined that can extract the local orientation of discontinuous signals as well as amplitude, orientation and phase structure of locally oscillatory signals. The full set of quaternionic wavelet functions are component by component orthogonal; their statistical properties are tractable, and forms for the variability of the estimators of the local phase and orientation are given, as well as the local energy of the image. By averaging estimators across wavelets, a substantial reduction in the variance is achieved